1. Technical Field
Embodiments of the subject matter disclosed herein generally relate to methods and systems and, more particularly, to mechanisms and techniques for removing noise from seismic data recorded underwater by a seismic receiver.
2. Discussion of the Background
Marine seismic data acquisition and processing generate an image of a geophysical structure (subsurface) under the seafloor. While this image/profile does not provide a precise location for oil and gas reservoirs, it suggests, to those trained in the field, the presence or absence of oil and/or gas reservoirs. Thus, providing a high resolution image of the subsurface is an ongoing process for the exploration of natural resources, including, among others, oil and/or gas.
A traditional marine system for recording seismic waves is illustrated in FIG. 1, and this system is described in European Patent No. EP 1 217 390, the entire content of which is incorporated herein by reference. In this document, plural seismic receivers 10 are removably attached to a pedestal 12 together with a memory device 14. Plural such receivers are deployed on the bottom 16 of the ocean. A source vessel 18 tows a seismic source 20 that is configured to emit seismic waves 22 and 24. Seismic waves 22 propagate downward, toward the ocean bottom 16. After being reflected from a structure 26, the seismic wave (primary) is recorded (as a trace) by the seismic receiver 10 while the seismic waves 24 reflected at the water surface 28 are detected by the receivers 10 at a later time. Since the interface between the water and air is well approximated as a quasi-perfect reflector (i.e., the water surface acts as a mirror for the acoustic or seismic waves), the reflected wave 24 travels back toward the receiver 10. This reflected wave is traditionally referred to as a ghost wave because this wave is due to a spurious reflection. The ghosts are also recorded by the receivers 10, but with a different polarization and a time lag relative to the primary wave 22. As the primary wave 22 moves in an upward direction toward the receiver 10, this wave is sometimes called up-going wave-field and as the ghost 24 moves in a downward direction toward the receiver 10, this wave is sometimes called down-going wave-field. Thus, in the following, the term up-going wave-field is used interchangeably with the term primary and the term down-going wave-field is used interchangeably with the term ghost.
FIG. 1 also shows the receiver 10 being configured to detach from the pedestal 12 and to float to the water surface 28 for collection by a collection boat 30. Based on the data collected by the receiver 10, an image of the subsurface is generated by further analyses of the collected data.
As discussed above, every arrival of a marine seismic wave at receiver 10 is accompanied by a ghost reflection. In other words, ghost arrivals trail their primary arrival and are generated when an upward-traveling wave is recorded a first time on submerged equipment before being reflected at the surface-air contact.
The time delay between an event and its ghost depends entirely upon the depth of the receiver 10 and the wave velocity in water (this can be measured and considered to be approximately 1500 m/s). It can be only a few milliseconds for towed streamer data (depths of less than 15 meters) or up to hundreds of milliseconds for deep Ocean Bottom Cable (OBC) and Ocean Bottom Node (OBN) acquisitions. The degenerative effect that the ghost arrival has on seismic bandwidth and resolution is known. In essence, interference between primary and ghost arrivals causes notches or gaps in the frequency content, and these notches cannot be removed without the combined use of advanced acquisition and processing techniques.
Such advanced processing techniques include wave-field separation or wave-field decomposition or deghosting. These techniques require advanced data acquisition, i.e., multi-component marine acquisition. Multi-component marine acquisition uses receivers that are capable of measuring at least two different parameters, for example, water pressure (recorded with a hydrophone) and water particle acceleration or velocity (recorded with a geophone or accelerometer). Thus, multi-component marine acquisitions deliver, besides a pressure recording P, at least a vertical particle velocity (or acceleration) component Z.
However, in OBC data processing, wave-field separation results are sometimes affected by high levels of noise on the vertical component Z, while the pressure component P is generally of good quality. Nonetheless, the Z component is needed to achieve complete pre-stack wave-field separation and also to drive processes such as mirror imaging and up-down deconvolution. Thus, there is a need to attenuate the noise on the Z component so that the wave-field separation results are not affected by the noise. Standard denoising techniques either rely on the noise being random (f-x-deconvolution, projection filtering, etc.) or that the noise is distinguishable in some other way (e.g., Radon demultiple discrimination on moveout).
For example, Craft, “Geophone noise attenuation and wavefield separation using multi-dimensional decomposition technique,” 70th EAGE conference, the entire content of which is incorporated herein by reference, uses local time-slowness (tau-p) transforms of the P and Z components in small overlapping windows for different frequency bands. The envelope of the Z energy is matched to the envelope of the P energy for each window/frequency band before the results are transformed back to the time-space (t-x) domain. It is noted that the seismic data is traditionally recorded in the t-x domain. While this method is effective at removing noise which is not present in the P-component, it has the disadvantage that the Z is scaled in amplitude to look like P, which is undesirable.
Another method is described in Zabihi et al., “Enhanced wavefield separation of OBC data,” 73rd EAGE conference and exhibition, the entire content of which is incorporated herein by reference. This method uses coherency-driven blending of data in the PZ summation process to attenuate noise on the Z-component.
However, the existing methods might not preserve the signal during the processing because it is known that any mathematical transformation used to manipulate the data from one domain to another domain introduces spurious features. In addition, if sparse transforms are not used, the areas of signal and coherent noise may overlap, thus, making it impossible to isolate the noise. Therefore, there is need of a method and system that overcome the afore-described drawbacks.